BIM existing buildings research examines why digital information management is harder when a project begins with incomplete records, uncertain geometry and assets that have changed over time. This guide shows you how to study adoption barriers systematically, connect them to measurable outcomes and design a dissertation that goes beyond a generic list of BIM challenges.
Why BIM existing buildings is a distinct research problem
New-build BIM workflows can begin from coordinated design information. Existing-building projects often begin from drawings, surveys, asset records and stakeholder knowledge that differ in age and reliability. Before BIM can support renovation or facilities management, teams must establish what exists, how accurate the evidence is and how much detail the model actually needs.
This makes BIM existing buildings a useful dissertation area because adoption depends on more than software. It involves data capture, modelling effort, interoperability, information governance, skills, client requirements and the business case for maintaining the model after creation.
Use BIM renovation projects, Scan-to-BIM and BIM information quality as related research resources.
Main challenges of BIM existing buildings adoption
Incomplete and outdated legacy information
Drawings may not represent later alterations. Asset registers may use inconsistent identifiers. Maintenance information may be stored separately from design information. Research can measure perceived reliability, verification effort or the number of discrepancies found when records are checked against site conditions.
Existing-condition survey requirements
Creating a reliable model can require measured survey, laser scanning, photogrammetry or intrusive investigation. Each method introduces cost, access constraints and uncertainty. A BIM existing buildings study can examine how survey strategy affects model quality or project confidence.
Modelling effort and fit-for-purpose detail
Existing geometry is often irregular. Modelling every detail can be expensive without improving the decisions under study. Research can compare high-detail and fit-for-purpose approaches using modelling time, file complexity, user ratings and decision usefulness.
Interoperability
Point clouds, authoring models, cost systems, energy models and facilities platforms may exchange information imperfectly. A dissertation can map where information is transformed, recreated or lost and assess the effect on workflow time or trust.
Model maintenance
A model loses value when building changes are not reflected. BIM existing buildings adoption therefore depends on update responsibility, information requirements and the systems used after a project ends.
Research questions for BIM existing buildings
Examples include: What factors predict BIM adoption intention among organisations managing existing buildings? How does legacy information quality influence modelling effort? How does reality-capture integration affect confidence in renovation coordination? What governance practices support the maintenance of BIM information during operation?
A quantitative study can test relationships among barriers, readiness and adoption. Interviews can explain why organisations decide that BIM is or is not worthwhile. Case studies can examine how evidence moves from existing records through survey, model creation, validation and use.
Conceptual framework for BIM existing buildings
A useful framework groups predictors into technological, organisational and project-context factors. Technology factors may include interoperability and capture capability. Organisational factors may include skills, leadership, standards and resources. Project factors may include building complexity, information availability and client requirements.
In plain English, this model estimates how several groups of factors are associated with an adoption outcome while allowing for unexplained variation.
Methodology for BIM existing buildings research
| Aim | Design | Evidence | Analysis |
|---|---|---|---|
| Rank adoption barriers | Survey | Practitioner ratings | Descriptive statistics |
| Test adoption predictors | Quantitative | Multi-item constructs | Reliability, correlation, regression |
| Understand implementation decisions | Interviews | Managers, surveyors, BIM practitioners | Thematic analysis |
| Evaluate one workflow | Case study | Records, surveys, models, issue logs | Triangulation |
See BIM dissertation methodology for a fuller justification process.
Measuring information readiness
Readiness can be operationalised through legacy-information completeness, survey capability, standards, staff competence, model-use requirements and update governance. Instead of asking whether an organisation is “ready,” create measurable dimensions.
This simple index averages defined readiness dimensions. The dimensions and weighting must be justified in your research rather than treated as a universal industry standard.
Worked example
Imagine an illustrative study comparing adoption-intention scores across low, medium and high information-readiness groups.
| Readiness group | Illustrative adoption score |
|---|---|
| Low | 36 |
| Medium | 65 |
| High | 91 |
Do not use these illustrative values as evidence. Real research must report sample characteristics, measurement quality and uncertainty.
Features of our BIM existing buildings research support
| Support area | What it covers | Responsible use |
|---|---|---|
| Topic design | Problem, question and scope | Adapt to your approved proposal |
| Questionnaire design | Constructs, items and pilot plan | Follow ethics requirements |
| Analysis guidance | Reliability, correlation, regression or themes | Keep your analysis auditable |
| Discussion planning | Interpret barriers and outcomes | Limit conclusions to your evidence |
- existing-building focus;
- adoption and readiness frameworks;
- quantitative and qualitative options;
- clear variables and analysis paths;
- academic-integrity guidance.
BIM existing buildings pricing
| Tier | Scope | Indicative price |
|---|---|---|
| Planning | Topic, questions and objectives | $— |
| Analysis support | Instrument and interpretation guidance | $— |
| Multi-stage support | Structured guidance across stages | $— |
See BIM research support pricing.
BIM existing buildings FAQs
Why is BIM harder for existing buildings?
Existing projects often begin with incomplete records, uncertain geometry and information created under different systems, so teams must establish a reliable baseline first.
Can I study adoption with a questionnaire?
Yes. Define constructs such as readiness, barriers, perceived value and adoption intention, then pilot and validate the instrument.
Is Scan-to-BIM necessary?
No. It is one possible approach to existing-condition capture. The appropriate method depends on the project and research question.
What is a good dependent variable?
Adoption intention, modelling effort, information quality, coordination effectiveness or model-use confidence are possible outcomes.
Can I study facilities management?
Yes. Model maintenance, asset-information completeness and information retrieval are strong operational research areas.
How do I avoid a broad topic?
Specify the building context, BIM process, participant group and outcome before finalising the title.
Build a defensible BIM existing buildings study
A strong BIM existing buildings dissertation explains why existing-condition information creates a specific adoption challenge, chooses evidence that can test that problem and avoids assuming that a digital model automatically creates value.
Advanced research design for BIM existing buildings
A rigorous BIM existing buildings study should distinguish readiness, implementation and realised use. Readiness concerns whether the organisation has the information, skills, standards and resources needed to begin. Implementation concerns how surveys, modelling, validation and information exchange are performed. Realised use concerns whether the model is actually used for coordination, cost planning, facilities management or another defined task.
This distinction prevents a common research problem: treating adoption as a yes-or-no variable. An organisation may have created models for selected assets but lack update routines, or may use BIM for renovation design without carrying information into operation. A better BIM existing buildings conceptual framework recognises stages and measures the capability at each stage.
Build a barrier and readiness framework
Group barriers into meaningful dimensions such as information, technology, people, process, commercial and client factors. Information barriers include missing records and uncertain conditions. Technology barriers include interoperability and data-processing capacity. People barriers include skills and role clarity. Process barriers include validation and update procedures. Commercial barriers include modelling effort and unclear return. Client factors include information requirements and long-term ownership.
These dimensions can become questionnaire constructs. Use several carefully worded items for complex constructs rather than one broad statement. Pilot the questionnaire with practitioners to check whether terms such as model maturity, information quality and readiness are understood consistently.
Sampling for BIM existing buildings studies
Participant selection should reflect the research question. Building surveyors may understand existing-condition uncertainty; BIM coordinators may understand model production and exchange; facilities teams may understand operational usefulness. Record participant role and experience so you can interpret differences rather than assuming all respondents have the same perspective.
For a quantitative BIM existing buildings survey, describe the recruitment method and limitations. Convenience and professional-network sampling can still produce useful evidence, but should not be presented as a random industry sample. For interviews, purposive sampling can target people who have managed implementation decisions or model maintenance.
Case-study design for BIM existing buildings
Case studies can trace the full information pathway from legacy records through survey, model creation, validation and use. Define the building, project stage and time period. Collect multiple evidence types where possible, such as drawings, model revisions, issue logs, meeting notes and interviews. This allows you to compare what participants say with what project records show.
A comparative case study can examine two buildings with different information readiness or BIM maturity. Establish comparison criteria in advance: modelling effort, number of verified discrepancies, issue-closure time, information retrieval or update performance. Explain contextual differences that may influence outcomes.
Reliability and validity in adoption questionnaires
Questionnaire research should demonstrate that the instrument measures the intended constructs. Content validity can be strengthened by grounding items in the literature and obtaining pilot feedback. Internal consistency can be assessed for multi-item constructs, but a reliable scale is not automatically valid. Interpret reliability alongside the conceptual definition.
For BIM existing buildings adoption research, avoid mixing barriers and outcomes in the same scale. For example, “high implementation cost” is a barrier, while “intention to adopt” is an outcome. Keeping constructs distinct improves the usefulness of correlation and regression results.
Quantitative analysis for BIM existing buildings
Begin with data cleaning and descriptive statistics. Check missing values, response distributions and coding. If you create composite constructs, verify that combining the items is defensible. Correlation can examine associations between readiness, barriers and adoption intention. Regression can estimate which predictors remain associated with adoption after other variables are considered.
Report effect sizes and uncertainty rather than focusing only on significance. A large sample can make small effects statistically detectable, while a small sample may hide meaningful patterns. Most cross-sectional BIM existing buildings studies should avoid causal claims because the variables are measured at one point in time.
Qualitative analysis for BIM existing buildings
Interview studies can explain why barriers persist even when technology is available. Code evidence related to information uncertainty, modelling effort, client requirements, skills, interoperability, governance and long-term maintenance. Develop themes that explain processes, such as “uncertain business case” or “model without ownership,” instead of merely ranking complaints.
Compare perspectives across roles. A designer may view the as-is model as successful after coordination, while an FM team may see limited value if asset attributes are incomplete or updates stop after handover. These differences can show that BIM existing buildings adoption is lifecycle-dependent.
Mixed methods and triangulation
A mixed-method design can use a survey to identify high-priority barriers and follow with interviews to explain them. Another approach can combine model-quality metrics with user feedback about usefulness. Integration should happen in the interpretation: explain where technical evidence and user perceptions agree or diverge.
Triangulation also strengthens case studies. If interviews claim that BIM reduced information-search time, compare that claim with workflow records or task observations where possible. Where evidence is unavailable, present the finding as a perception rather than an objective performance result.
Ethics and information governance
Existing-building studies may involve client documents, asset records or project files that are not intended for public distribution. Collect only what your approved study needs, anonymise identifiers where appropriate and follow your university requirements for storage and retention. Do not reproduce project material without permission.
Responsible research also requires transparency. Keep a record of exclusions, data transformations, coding decisions and statistical procedures. Academic support should help you understand the process, not conceal how the analysis was performed.
Writing the discussion chapter
Organise the discussion around objectives. For each finding, compare it with previous BIM adoption research, explain possible mechanisms and identify alternative explanations. If information readiness predicts adoption intention, consider whether organisations with stronger management capability may also have more resources for digital investment.
Practical recommendations should be specific. Instead of saying “organisations should use BIM,” your evidence may support recommendations such as defining existing-information requirements before modelling, assigning model-update responsibility, using fit-for-purpose detail or integrating verification into the workflow.
BIM existing buildings research-quality checklist
- Define adoption as stages or capabilities rather than a simple yes/no label.
- Separate readiness, barriers, implementation and outcomes.
- Recruit participants with relevant existing-building experience.
- Map each survey item to a defined construct.
- Plan the analysis before distributing the instrument.
- Use case evidence to verify perceptions where possible.
- Distinguish model creation from model maintenance.
- Report limitations and alternative explanations.
- Avoid causal claims from cross-sectional data.
- Keep recommendations directly linked to findings.
Following this checklist helps BIM existing buildings research explain why adoption succeeds or fails and which information-management capabilities are most important for long-term value.